In a typical packaging line, comprising a filling machine, where packages are filled with foodstuff or other content that is associated with very low tolerance regarding, e.g., bacteria content, a schedule or plan should exist according to which an operator takes package samples from the packaging line for incubation and sterility analysis. During such analysis the vast majority of the samples are typically found sterile. Nevertheless, when an unsterile sample is found during such sampling and analysis, this triggers some kind of action. Such actions may be an inspection of a warehouse in which the packages from the packaging line have been stored and subsequent re-sampling of the stored packages.
Typically, a sampling plan specifies obtaining a few samples at regular time intervals, this is a so called “random sampling”. Samples may also be obtained every time a steady state of a filling machine is disturbed, this is a so called “aimed sampling” or “sampling at events”. Typical events that trigger such aimed sampling may be production start or re-start after a stop, splicing of materials making up the packages, change of filling product, and many others depending on, e.g., previous history of the machinery in the packaging line and depending on the requirements of the specific user of the packaging line.
Furthermore, a typical sampling plan may involve sampling and analyzing the samples in a destructive way from 1 up to 10 samples per 1000 produced packages. This may mean obtaining some 100 to 1000 packages per packaging line per day, assuming a daily production rate of 100 000 packages. An ordinary overall defect (e.g. in the form of bacterial contamination) rate, unless an extraordinary event or “crisis” occurs, is well below 1 defect sample in 1000 samples. In other words, a normal occurrence of defects in the samples does not exceed a few units per packaging line per month.
Very often no record is kept of the large amount of sampled packages that are found to be sterile, and only the very few non-sterile packages are recorded. This is explainable by understanding the large administrative effort that would be needed to register and classify hundreds of packages sampled per filling machine per day, which are generally sterile, with the exception of a very few contaminated packages that are found maybe once per week.
However, in this situation a lot of information is lost, and specifically the “denominator” of the definition of aseptic performance is missing or loosely defined. In particular, it is difficult to identify specific situations (periods, lines, organization set-ups, operational modes etc.) which may potentially be connected with higher or lower aseptic performance; thus potential causes for particularly bad (or good) aseptic performance are difficult to identify and the effectiveness of possible corrective actions cannot be verified on objective basis. Moreover, typically not much effort is spent in studying quality trends, or it is done but on the basis of uncertain or unreliable data. Prior art systems and methods are thus incapable of making use of the mass of accumulated data in order to maintain or improve the quality level of the output from the packaging line.